Empirical Studies in Consumption, House Prices and the Accuracy of European Growth and ...

148 Pages·2007·1.45 MB·English

by  Bharat Barot

Empirical Studies in Consumption,
House Prices and the Accuracy of
European Growth and Inflation
Forecasts
Bharat Barot

Working Paper No. 98, Dec 2006
Published by
The National Institute of Economic Research
Stockholm 2006
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Abstract

BAROT, Bharat, This Ph.D. thesis, Empirical Studies in Consumption, House Prices and the
Accuracy of European Growth and Inflation Forecasts contains four self-contained chapters:

Chapter I gives a brief introduction to the topic of the thesis and summarizes the main results.

Chapter II an aggregated consumption function based on the life cycle hypothesis using the error
correction methodology is estimated for Sweden. Wealth in its disaggregated form (financial and
housing wealth) is incorporated in the consumption function, along with basic standard
explanatory variables including the unemployment variable. Applying Hendry’s general to
specific modelling strategy one final model is deduced. The study finds that each of the primary
components of wealth has an equal role for consumer’s expenditure. In addition the study finds
significant effects from employment and interest rates.

Chapter III a stock-flow model serves as the theoretical basis for the fundamental determinants
of real estate construction and prices. A housing market model for Sweden has been estimated on
semi-annual data for 1970-1998 by separately modelling the demand and the supply sides,
specified in error correction form. The supply side is based on Tobin’s q-index. The results
indicate that even in a turbulent period, Swedish house prices and housing investment are tracked
quite well with this specification. The importance of the simulations and their usefulness to
Swedish policy makers is discussed. Both ex post and ex ante forecasts using the model gives
reasonable results.

Chapter IV (with Zan Yang), we estimate quarterly dynamic housing demand and investment
supply models for Sweden and the UK for the sample period 1970-1998, using an Error
Correction Method (ECM). In order to facilitate comparisons of results between Sweden and the
UK we model both countries similarly using comparable exogenous variables. The long run
income elasticity for Sweden and the UK are both constrained to be equal to one. The long run
semi-elasticity for interest rate is 2.1 for Sweden and 0.9 for the UK. The speed of adjustment on
the demand side is 12% and 23% for Sweden and the UK, respectively, while on the supply side
it is 6% and 48%. Tobin’s q Granger causes housing investment.

Chapter V (with Lars-Erik Öller), evaluates the one-year ahead forecasts by the OECD and by
national institutes of GDP growth and inflation in 13 European countries. RMSE was large 1.9%
for growth and 1.6% for inflation. Six (11) OECD and ten (7) institute growth forecasts records
were significantly better than an average growth forecast (the current year forecast). All full
record-length inflation forecasts were significantly better than both naive alternatives. There were
no significant differences in accuracy between the forecasts of the OECD and the institutes. Two
forecasts were found to be biased and one had auto-correlated errors.
CONTENTS
ACKNOWLEDGEMENTS....................................................................................................................................6
CHAPTER I............................................................................................................................................................8
INTRODUCTION TO THE THESIS.............................................................................................................................8
REFERENCES.......................................................................................................................................................10
CHAPTER II.........................................................................................................................................................11
THE ROLE OF WEALTH IN THE AGGREGATED CONSUMPTION FUNCTION USING AN ERROR
CORRECTION APPROACH: SWEDISH EVIDENCE FOR THE YEARS 1970 – 1993...................................11
1. INTRODUCTION...............................................................................................................................................11
2. REVIEW OF EARLIER STUDIES..........................................................................................................................11
3. THE MAIN OBJECTIVE OF THIS STUDY..............................................................................................................12
4. THE STEADY STATE WEALTH MODEL AND THE LIFE CYCLE THEORY................................................................13
5. EXPLANATORY VARIABLES.............................................................................................................................16
5.1 Disposable income.................................................................................................................................16
5.2 Inflation..................................................................................................................................................17
5.3 The real after tax interest rate.................................................................................................................17
5.4 Wealth....................................................................................................................................................17
5.5 House prices...........................................................................................................................................18
5.6 Value added tax......................................................................................................................................18
5.7 Other Dummies......................................................................................................................................18
5.8 Unemployment.......................................................................................................................................18
5.9 The data set............................................................................................................................................19
6. ECONOMETRIC METHODS................................................................................................................................19
6.1 The error-correction method..................................................................................................................20
6.1 Integration..............................................................................................................................................22
6.3 Cointegration..........................................................................................................................................23
6.4 The general to specific approach............................................................................................................23
7. FORECASTING PERFORMANCE.........................................................................................................................25
7.2 Recursive estimates of stability..............................................................................................................29
7.3 Lagrange multiplier test.........................................................................................................................29
7.4 The Akaike and the Bayesian information criteria for nested model.....................................................29
7.5 Test for exogeneity.................................................................................................................................32
TABLE 10. EXOGENEITY, TESTS ON THE SIGNIFICANCE OF EACH VARIABLE........................................................34
7.6 Comparisons with Berg and Bergström (1993)......................................................................................34
8. COMPARATIVE STATICS AND DYNAMIC SIMULATIONS WITH THE CONSUMPTION FUNCTION............................36
8.1 Equilibrium (steady state)......................................................................................................................36
8.2 Comparative statics................................................................................................................................36
8.3 Dynamics...............................................................................................................................................37
9 CONCLUSIONS..................................................................................................................................................38
REFERENCES.......................................................................................................................................................39
APPENDIX 1. THE REAL SAVING RATE.................................................................................................................44
APPENDIX 2: DYNAMIC SIMULATIONS................................................................................................................45
APPENDIX 3. PLOTS OF THE DATA SET................................................................................................................49
LIST OF VARIABLES............................................................................................................................................53
CHAPTER III.......................................................................................................................................................55
A FULL FLEDGED DEMAND-SUPPLY ECONOMETRIC MODEL FOR SWEDISH PRIVATE HOUSING FOR THE PERIOD
(1970 - 2000)......................................................................................................................................................55
1. INTRODUCTION...............................................................................................................................................55
2. EARLIER STUDIES............................................................................................................................................56
3. A FRAMEWORK FOR ANALYSIS........................................................................................................................56
3.1 The long run demand side of the equation.............................................................................................56
3.2 The long run supply side of the equation...............................................................................................57
4. DATA AND THE EXPLANATORY VARIABLES.....................................................................................................58
5. ECONOMETRIC METHODOLOGY.......................................................................................................................59
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6. THE DEMAND SIDE RESULTS – REAL HOUSE PRICES.........................................................................................59
7. THE SUPPLY SIDE RESULTS - HOUSING INVESTMENT........................................................................................60
7.1 The long run housing demand and supply..............................................................................................61
7.2 The long run price and quantity of housing............................................................................................68
8. CONTROVERSY OF THE CAUSES OF THE CRISIS IN THE SWEDISH HOUSING MARKET.........................................69
9. SIMULATIONS AND HOUSING POLICY ISSUES...................................................................................................71
10. SIMULTANEOUS MODEL SOLUTION................................................................................................................74
11. THE HOUSE PRICE FORECAST AND PROJECTIONS 1999-2000.........................................................................77
12. CONCLUSIONS...............................................................................................................................................79
REFERENCES.......................................................................................................................................................80
APPENDIX 1. INTEGRATION, AND COINTEGRATION.............................................................................................82
APPENDIX 2.WEAK EXOGENEITY........................................................................................................................84
APPENDIX 3. SWEDISH DATA..............................................................................................................................88
CHAPTER IV.......................................................................................................................................................89
THE STOCK- FLOW MODEL FOR SWEDEN AND THE UNITED KINGDOM. ECONOMETRIC ANALYSIS FOR THE PERIOD
1970 – 1998........................................................................................................................................................89
1. INTRODUCTION...............................................................................................................................................89
2. REVIEW OF EARLIER STUDIES..........................................................................................................................90
3. THEORETICAL CONSIDERATIONS.....................................................................................................................91
3.1 The long run demand side of the equation.............................................................................................91
3.2 The long run supply side of the equation...............................................................................................92
4. DATA..............................................................................................................................................................93
5. ECONOMETRIC METHODOLOGY.......................................................................................................................94
5.1 Integration..............................................................................................................................................94
5.2 Cointegration..........................................................................................................................................94
5.3 Estimation..............................................................................................................................................95
6. PRESENTATION OF RESULTS............................................................................................................................96
6.1 The demand side Sweden and the UK....................................................................................................96
6.2 The supply side Sweden and the UK....................................................................................................102
7. FORECASTING ABILITY..................................................................................................................................106
8. GRANGER CAUSALITY...................................................................................................................................107
9. CONCLUSIONS...............................................................................................................................................109
REFERENCES.....................................................................................................................................................111
APPENDIX 1. INTEGRATION AND COINTEGRATION............................................................................................115
APPENDIX 2. DATA AND DATA SOURCES FOR SWEDEN.....................................................................................118
APPENDIX 3 DATA AND DATA SOURCES FOR THE UK.......................................................................................119
CHAPTER V.......................................................................................................................................................120
THE ACCURACY OF EUROPEAN GROWTH AND INFLATION FORECASTS..............................................................120
1. INTRODUCTION.............................................................................................................................................120
2. DATA ...........................................................................................................................................................121
3. ROOT MEAN SQUARED ERRORS AND NAIVE FORECASTS................................................................................121
4. WEAK FORM INFORMATIONAL EFFICIENCY...................................................................................................124
5. DIRECTIONAL FORECASTS.............................................................................................................................125
6. STATISTICAL ERRORS....................................................................................................................................127
7. CONCLUSION AND DISCUSSION.....................................................................................................................127
ACKNOWLEDGEMENTS.....................................................................................................................................128
REFERENCES.....................................................................................................................................................129
APPENDIX 1. NATIONAL INSTITUTES FORECAST DATE......................................................................................131
APPENDIX 2. THE CONTINGENCY TABLE TEST OF DIRECTIONAL ACCURACY.....................................................143
TITLES IN THE WORKING PAPER SERIES..................................................................................................144
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Acknowledgements
The main part of this dissertation was written during my time as economist at the National
Institute of Economic Research (NIER), whose hospitality is gratefully acknowledged. Even a
cursory look at the contents of this thesis should suffice for the reader to gather that I have been
deeply influenced by the stimulating atmosphere and trends at NIER. In the initial period of my
employment at NIER, I devoted a great deal of my time to studies of private consumption in
Sweden, which resulted into an NIER Working paper “On Determinants of Private Consumption
in Sweden” in 1993, co-authored with Alfred Kanis. In this study quarterly and semi-annual
functions for total private consumption expenditures, cars, semi & other durables, and nondurable
consumption where estimated using Error Correction models (ECM). This study was supported
by the Economic Council of the National Institute of Economic Research (1992-1993).
At that time I was enrolled on the doctoral program at the Department of Economics at
Stockholm University. My supervisor then was Göran Eriksson who unfortunately passed away
in 1994. I immediately took contact with Prof. Peter Englund than at Uppsala University to be my
supervisor for my Licentiate Degree in Economics awarded to me 1995 writing the paper “The
Role of Wealth in the Aggregate Consumption Function using an Error Correction Approach:
Swedish evidence from the years 1970 – 1993”.
The major econometric models both for Sweden and UK do now incorporate housing wealth
alongside with financial wealth in their consumption functions, see Hendry et al. (1981), Berg
(1993 ), Kanis and Barot (1993) and Barot (1995). This makes it more important to have an
econometric model which increases our understanding of the determinants of house prices and of
effects on house prices of both fiscal and monetary policies. This obviously made me transmit
into issues related to house prices and real estate economics. In 1997 the Department of Real
Estate and Construction Management Royal Institute of Technology arranged a graduate course
in real estate economics given by Professors John Quigley and Nancy Wallace from the
University of Berkeley. With guidance from Professors John Quigley, Nancy Wallace and finally
Alfred Kanis, I was able to write my second paper in this dissertation “A Full Fledged Demand-
Supply Econometric Model for Swedish Private Housing (1970-2000)“. Thanks to both
Professors Peter Englund and Roland Andersson and the staff at the Department of Real Estate
and Construction Management for supporting my financial my trip to attend the AREUEA
conference in Maui, Hawai during the year 1999. A recent paper on "The Stock-Flow Model for
Sweden and the United Kingdom: Econometric Analysis for the period 1970-1998”, has been
written in collaboration with Dr. Zan Yang formerly at the (Department. of Building and Real
Estate Economics, Department of Infrastructure, Royal Institute of Technology (KTH), Sweden,
but now at Institute for Housing and Urban Research, Uppsala University, Gävle, Sweden.
During the year 1998 Svante Öberg was appointed the new director of the National Institute of
Economic Research. He was very interested on the issue of the accuracy of NIER forecasts. I was
in the initial stage requested to check the accuracy of NIER’s GDP forecasts. This project was
then extended to cover the accuracy of both the European GDP and inflation forecasts. This was
joint work with Professor Lars-Erik Öller who has been the head of the Research Department
(1993-2001). This led to publication of two working paper in the NIER’s Working Paper Series
and also to the publication in the International Journal of Forecasting 16, (2000) 293-315.
I would like to thank both of my supervisors Professor Bengt Turner and Professor Thomas
Lindh who have given me this opportunity in pursuing this thesis. Their help kindness and
concern is highly appreciated. Constructive and critical comments by Mats Wilhelmsson, my
opponent at my final seminar held at Uppsala University on 27th of September 2002 are also
highly appreciated. I also would like to thank Niklas Ahlgren for reading all the four papers and
coming up with valuable suggestions on each paper. Jukka Nybloms comments on one of the
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papers are highly appreciated too. Thanks to Dr. Robert D Campbell willing to be my discussant.
The anonymous referees for the European Journal of Housing Policy, Review of Urban &
Regional Development Studies, and finally the International Journal of Forecasting have also
come with critical comments which have also helped to improve the quality of the published
papers.
Finally I would like to thank in particular Alfred Kanis, Parameswar Nandakumar, Kanak
Patel, Zan Yang, Manuch Irandoust, Petter Lundvik, Jan Alsterlind, Mats Kinwall, Tommy
Persson, Iwona Stankiewicz, Ingillil Sjoblom, Lena Hamilton, Birgit Kaur, Marianne Larson,
Lars Johansson, Anneli Hedlund, Alf Carling, Roger Knudsson, Sven Hellroth, Hans-Roland
Johnsson, Patrik Eriksson, Lasse Koskinen, and Hans-Martin Krolzig, Karl-Gustav Hansson,
Peter Englund, Lars Erik Öller, Hans Lindberg, Camilla Holmen, Tomas Forsfält, Ann Öberg,
Tomas Lindström, Göran Hjelm, Jonny Nilsson, Dag Stålfors, Ing-Marie Gren, Lisa Svensson,
Eva Samakovlis, Gunnar Öhman, Magnus Sundqvist, Anders Wallberg, and finally Göran
Östblom for their encouragement and support in pursuing this thesis. Tarane Barot, Shabane
Barot, Rahima Ahrary, Jagdish Barot, Rohit Barot, Ravindra Barot, Ashok Barot, Meena Barot,
Aruna Barot, Ambalal and Kalavati Barot have always been with me in my spirits. There are
many who I might have forgotten to mention who have been valuable in one way or another. To
all of you I dedicate this thesis too.

It is the God of small things that matter in life.

Bharat Barot
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Chapter I
Introduction to the thesis
This thesis consists of four separate chapters on Empirical studies in Consumption, House Prices
and the Accuracy of European Growth and Inflation Forecasts. The first three chapters in some
respects have the same theme and essentially about problems related to consumption. An
aggregated consumption function relates total consumption to the level of income and wealth and
perhaps other variables. Consumption functions are sometimes defined for individual households,
but their major role is determining total national consumption in a macro economic model. The
relationship was first defined by J. M. Keynes (1936) and it is a major element in his model of
income determination. One characteristic of the consumption function, the marginal propensity to
consume, is an important determinant of the stability of the economy in simple models of the
multiplier type. The consumption function was widely used until the early 1950s when more data
and improved statistical techniques demonstrated its inadequacy. In attempting to quantify the
relationship, it was observed that there is often considerable short-run variation in consumption
which is not accounted for by changes in income, but that when income and consumption are
measured in longer run averages, there is a close relationship. The failure of variation in income
in accounting for variation in consumption suggested that other influences, such as the value of
wealth would be important.
The first chapter deals with the issue of the role of wealth in the aggregated consumption
function for Sweden using the Error correction Model (ECM). The results indicate that both
components of wealth (financial and housing) have an equal role. One dominant theme to arise
from this assessment of the adequacy of the previously dominant consumption functions has been
the role of wealth, and in some cases more particularly housing wealth, in an explanation of
aggregated expenditure. The concept of an Error Correction Model dates back at least to the
paper by Sargan (1964), on wages and prices in the UK. However the current popularity of these
models owes much to their association with the work of Hendry (1980) and his promotion of the
general-to-specific approach to econometric modelling. The major econometric models both of
the UK and Sweden do now incorporate housing wealth along with financial wealth in their
consumption functions. This makes it all more important to have an econometric model which
increases our understanding of the determinants of house prices.
The second chapter is connected to the first in the sense that we endogenize house prices
applying the stock-flow model. Muth (1960) developed a stock-adjustment framework that has
long served as the basic framework in which to model housing markets In a stock-adjustment
model, differences between desired or optimal demand and the and the existing stock lead to an
adjustment process that, in the end, equates the two. The stock-adjustment model is demand-
oriented; investment in new housing is derived from shifts in demand rather than from explicit
profit maximisation by building companies. Poterba (1984) develops an asset-market model. On
the demand side consumers equate discounted marginal benefits from housing services to
marginal user cost. On the supply side Poterba does not make any explicit assumption about the
objectives of the building firms, but he specifies a cost function in which the level of investment
is a function of a number of cost variables. To close the system, he specifies how stocks relate to
flows in the model.
To analyse the aggregate effects of changes in house prices upon the value of total stock of
housing we need to model how such changes affects total demand for housing and we also need
to specify how the supply of private homes is determined. Simply written we are trying to sort out
the mechanism in the housing market for private homes in Sweden, distinguishing between cause
and effect; between exogenous and endogenous factors- is crucial if we are to understand the
economics of housing. We derive a reduced form for the stock-flow model for Sweden. The
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reduced form approach specifies separate housing demand and supply equations and then equates
the two to derive a price equation. In addition we conduct both ex post and ex ante forecasts for
private house prices for Sweden. The ex ante forecasts compared to the outcomes look promising.
Private house prices for Sweden can be ex post and ex ante forecasted.
The third chapter is a continuation of the theme from the second chapter but with an
international perspective. International comparisons of house price and housing trends have been
dogged by data problems. In the third paper we estimate dynamic housing demand and
investment supply models for Sweden and the UK for the sample period 1970-1998, using an
Error Correction Method (ECM). In order to facilitate comparisons of results between Sweden
and the UK we model both countries similarly using comparable exogenous variables. We
compare the short and the long-term point estimates, elasticities and the error correction speed of
adjustment coefficients. The secondary objective is to investigate if changes in house prices and
housing investment can be ex post forecasted? The results indicate many similarities and a few
differences. Ex post forecasts look promising.
The fifth chapter is autonomous. Considerable intellectual activity within the economics
profession is devoted to the production, interpretation and analysis of forecasts of major
economic variables. The main purpose of most macroeconomic forecast is as an aid to the
rational discussion of economic policy making. Forecasts of economic variables are important
because governments plan budgets and set macroeconomic policies based on forecasts of future
economic activity e.g. money, stock and foreign exchange markets consumption and investment.
There are many reasons for studying the accuracy of the economic forecasts, including the need
to: (1) identify the sources and thereby the causes of major mistakes, in order to learn from them
(2) form a rational basis for assessing what kind of policy the accuracy typically permits policy
makers to make (3) be able to recognize in advance the occasion when there is a conjunction of
the sort of circumstances that typically lead to large forecasting errors (see Chatfield (2001)).
The analysis in the fifth chapter indicates that the one year ahead forecasts both by the OECD
and by national institutes of GDP growth and inflation in 13 European countries that the Root
mean square error was large: 1.9% for growth and 1.6% for inflation. There was no significant
difference in accuracy between the forecasts of the OECD and the national institutes. Positively
biased revisions reveal large errors in data.
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References
Hendry, D. F., 1993, Econometrics: Alchemy or Science? , Blackwell Publishers UK,
Chatfield, C., 2001, Time Series Forecasting, London, Chapman and Hall.
Keynes, J.M., 1936, The General Theory of Employment, Interest and Money, London,
Macimillian and Co. Ltd.
Muth, R. F., 1960, The Demand for Non-Farm Housing, In: Harberger, A., (eds.), The demand
for durable goods, Chicago, University of Chicago Press, 29-96.
Poterba, J.M., 1984, Tax subsidies and owner-occupied housing: an asset-market approach,
Quarterly Journal of Economics 99, pp. 729-752.
Sargan, J. D., 1964, Wages and Prices in the United Kingdom: A Study in Econometric
Methodology, in Econometric Analysis for National Planning, (eds.), Hart, P.E., Mills,
G. and Whitaker, J.K., London: Butterworths.
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